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Abu can help users to improve the strategy automatically, take the initiative to analyze the behavior of the orders generated by the strategy to prevent the losing-money transaction.
Right now, we still writting code by hand, abu is designed to be running complete-automatically in the future, including the entire work-process and strategy itself.
Our expectations : abu users only need to provide some seed strategy, on the basis of these seeds, computer continue to self-learning, self-growth, to build a new strategy which can adjust its parameters with the time series data.
Content | Path |
---|---|
Abu Quantitative Trading System | ./abupy |
Abu Quantitative Trading Tutorial | ./abupy_lecture |
《量化交易之路》 (The Road of Quantitative Trading) example code | ./ipython and ./python |
《机器学习之路》 (The Road of Machine Learning) example code | https://github.com/maxmon/abu_ml |
https://www.abuquant.com/abu_context/output_cn_week_2022-10-10/report/sh000001/index.html
https://www.abuquant.com/abu_context/output_cn_day_2022-10-11-00-25-15/report/sh000001/index.html
https://www.abuquant.com/abu_context/output_cn_week_2022-10-16/report/sz399001/index.html
https://www.abuquant.com/abu_context/output_cn_day_2022-10-12-13-40-48/report/sz399001/index.html
https://www.abuquant.com/abu_context/output_us_week_2022-10-11/report/us.DJI/index.html
https://www.abuquant.com/abu_context/output_us_day_2022-10-11-01-26-56/report/us.DJI/index.html
https://www.abuquant.com/abu_context/output_hk_week_2022-10-10/report/hkHSI/index.html
https://www.abuquant.com/abu_context/output_hk_day_2022-10-10-23-27-08/report/hkHSI/index.html
Recommended to use Anaconda to deploy the Python environment, see here
import abupy
More examples of UI operations
Section 1 UI operation tutorial
Trading strategy decide when to invest, backtesting tell us the simulation of profit about this strategy in the historical data.
Through stop loss and profit cap to keep profit generated by the strategy, lower risk.
Consider slippage and transaction costs on applying the strategy
type | date | symbol | commission |
---|---|---|---|
buy | 20150423 | usTSLA | 8.22 |
buy | 20150428 | usTSLA | 7.53 |
sell | 20150622 | usTSLA | 8.22 |
buy | 20150624 | usTSLA | 7.53 |
sell | 20150706 | usTSLA | 7.53 |
sell | 20150708 | usTSLA | 7.53 |
buy | 20151230 | usTSLA | 7.22 |
sell | 20160105 | usTSLA | 7.22 |
buy | 20160315 | usTSLA | 5.57 |
sell | 20160429 | usTSLA | 5.57 |
Backtesting on multiple stocks, control position to lower risk.
A good trading strategy needs a good stock.
Good metric give you right direction.
By customizable scoring, seek the best parameter for strategy.Like:how many days should be on MA?
How to use machine learning technology correctly in quantitative trading of investment goods?
Technical analysis is based on three assumptions:1. The market discounts everything.2. Price moves in trends.3. History tends to repeat itself.
Behind similar investment trend, it is often with similar investment groups.
Search and analyze failed orders generated by strategy, intercept possible failing orders by the ump .
The design goals of ump module are:
Abu support stock, futures, digital coins and other financial investment. Abu support quotes query and transactions, and also offer a high degree of customization.
More abu quantitative tutorial please pay attention to our WeChat public number: abu_quant
Also any questions, please contact my personal WeChat number:
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